Locating shifts in phenotypic evolutionary rates
The function search.shift (Castiglione et al.
2018) tests whether individual clades or isolated tips dispersed through
the phylogeny evolve at different RRphylo rates as compared
to the rest of the tree. Instances of rate shifts may be automatically
found.
search.shift(RR, status.type = c("clade", "sparse"),node = NULL, state
= NULL, cov = NULL, nrep = 1000, f = NULL,foldername)RR |
an object fitted by the function |
status.type |
whether the |
node |
under the |
state |
the state of the tips specified under the |
cov |
the covariate to be indicated if its effect on rate values must be
accounted for. Contrary to |
nrep |
the number of simulations to be performed for the rate shift
test, by default |
f |
the size of the smallest clade to be tested. By default, nodes subtending to one tenth of the tree tips are tested. |
foldername |
the path of the folder where plots are to be found. |
The function search.shift takes the object produced by
RRphylo. Two different conditions of rate change can be
investigated. Under the "clade" condition the vector of node or
nodes subjected to the shift must be provided. Alternatively, under the
"sparse" case the (named) vector of states (indicating which tips
are or are not evolving under the rate shift according to the tested
hypothesis) must be indicated. In the "clade" case, the function may
perform an 'auto-recognize' feature. Under such specification, the function
automatically tests individual clades (from clades as large as one half of
the tree down to a specified clade size) for deviation of their rates from
the background rate of the rest of the tree, which is identical to the
"clade" case. An inclusive clade with significantly high rates is
likely to include descending clades with similarly significantly high
rates. Hence, with 'auto-recognize' the search.shift function is
written as to scan clades individually and to select only the node
subtending to the highest difference in mean absolute rates as compared to
the rest of the tree. A plot of the tree highlighting nodes subtending to
significantly different rates is automatically produced. Caution must be
put into interpreting the 'auto-recognize' results. For instance, a clade
with small rates and another with large rates could be individuated even
under BM. This does not mean these clades are actual instances for rate
shifts. Clades must be tested on their own without the 'auto-recognize'
feature, which serves as guidance to the investigator, when no strong a
priori hypothesis to be tested is advanced. The 'auto-recognize' feature is
not meant to provide a test for a specific hypothesis. It serves as an
optional guidance to understand whether and which clades show significantly
large or small rates as compared to the rest of the tree. Individual clades
are tested at once, meaning that significant instances of rate variation
elsewhere on the tree are ignored. Conversely, running the "clade"
condition without including the 'auto-recognize' feature, multiple clades
presumed to evolve under the same shift are tested together, meaning that
their rates are collectively contrasted to the rest of the tree, albeit
they can additionally be compared to each other upon request. Under both
the "clade" and "sparse" conditions, multiple clades could be
specified at once, and optionally tested individually (for deviation of
rates) against the rates of the rest of the tree and against each other.
The histogram of random differences of mean rates distribution along with
the position of the real difference of means is automatically generated by
search.shift. Regardless of which condition is specified, the
function output produces the real difference of means, and their
significance value.
Under all circumstances, search.shift provides a vector of
$rates. If 'cov' values are provided, rates are regressed
against the covariate and the residuals of such regression form the vector
$rates. Otherwise, $rates are the same
rates as with the RR argument.
Under "clade" case without specifying nodes (i.e.
'auto-recognize') a list including:
$all.clades for each detected node, the data-frame includes
the average rate difference (computed as the mean rate over all branches
subtended by the node minus the average rate for the rest of the tree) and
the probability that it do represent a real shift. Probabilities are
contrasted to simulations shuffling the rates across the tree branches for
a number of replicates specified by the argument nrep. Note that the
p-values refer to the number of times the real average rates are larger (or
smaller) than the rates averaged over the rest of the tree, divided by the
number of simulations. Hence, large rates are significantly larger than the
rest of the tree (at alpha = 0.05), when the probability is > 0.975; and
small rates are significantly small for p < 0.025.
$single.clades the same as with 'all.clades' but restricted to the largest/smallest rate values along a single clade (i.e. nested clades with smaller rate shifts are excluded). Large rates are significantly larger than the rest of the tree (at alpha = 0.05), when the probability is > 0.975; and small rates are significantly small for p < 0.025.
Under "clade" condition by specifying the node
argument:
$all.clades.together if more than one node is tested, this specifies the average rate difference and the significance of the rate shift, by considering all the specified nodes as evolving under a single rate. As with the 'auto-recognize' feature, large rates are significantly larger than the rest of the tree (at alpha = 0.05), when the probability is > 0.975; and small rates are significantly small for p < 0.025.
$single.clades this gives the significance for individual clades, tested separately. As previously, large rates are significantly larger than the rest of the tree (at alpha = 0.05), when the probability is > 0.975; and small rates are significantly small for p < 0.025.
Under the "sparse" condition:
$state.results for each state, the data-frame includes the average rate difference (computed as the mean rate over all leaves evolving under a given state, minus the average rate for each other state or the rest of the tree) and the probability that the shift is real. Large rates are significantly larger (at alpha = 0.05), when the probability is > 0.975; and small rates are significantly small for p < 0.025. States are compared pairwise.
Pasquale Raia, Silvia Castiglione, Carmela Serio, Alessandro Mondanaro, Marina Melchionna, Mirko Di Febbraro, Antonio Profico, Francesco Carotenuto
Castiglione, S., Tesone, G., Piccolo, M., Melchionna, M., Mondanaro, A., Serio, C., Di Febbraro, M., & Raia, P.(2018). A new method for testing evolutionary rate variation and shifts in phenotypic evolution. Methods in Ecology and Evolution, 9: 974-983.doi:10.1111/2041-210X.12954
## Not run:
data("DataOrnithodirans")
DataOrnithodirans$treedino->treedino
DataOrnithodirans$massdino->massdino
DataOrnithodirans$statedino->statedino
RRphylo(tree=treedino,y=massdino)->dinoRates
# Case 1. Without accounting for the effect of a covariate
# Case 1.1 "clade" condition
# with auto-recognize
search.shift(RR=dinoRates,status.type="clade",foldername=tempdir())
# testing two hypothetical clades
search.shift(RR=dinoRates,status.type="clade",node=c(696,746),foldername=tempdir())
# Case 1.2 "sparse" condition
# testing the sparse condition.
search.shift(RR=dinoRates,status.type= "sparse",state=statedino,foldername=tempdir())
# Case 2. Accounting for the effect of a covariate
# Case 2.1 "clade" condition
search.shift(RR=dinoRates,status.type= "clade",cov=massdino,foldername=tempdir())
# Case 2.2 "sparse" condition
search.shift(RR=dinoRates,status.type="sparse",state=statedino,cov=massdino,
foldername=tempdir())
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.